{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ApdaLD4Qi30H"
      },
      "source": [
        "# Neo4j as Graph Memory"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l7bi3i21i30I"
      },
      "source": [
        "## Prerequisites\n",
        "\n",
        "### 1. Install Mem0 with Graph Memory support\n",
        "\n",
        "To use Mem0 with Graph Memory support, install it using pip:\n",
        "\n",
        "```bash\n",
        "pip install \"mem0ai[graph]\"\n",
        "```\n",
        "\n",
        "This command installs Mem0 along with the necessary dependencies for graph functionality.\n",
        "\n",
        "### 2. Install Neo4j\n",
        "\n",
        "To utilize Neo4j as Graph Memory, run it with Docker:\n",
        "\n",
        "```bash\n",
        "docker run \\\n",
        "  -p 7474:7474 -p 7687:7687 \\\n",
        "  -e NEO4J_AUTH=neo4j/password \\\n",
        "  neo4j:5\n",
        "```\n",
        "\n",
        "This command starts Neo4j with default credentials (`neo4j` / `password`) and exposes both the HTTP (7474) and Bolt (7687) ports.\n",
        "\n",
        "You can access the Neo4j browser at [http://localhost:7474](http://localhost:7474).\n",
        "\n",
        "Additional information can be found in the [Neo4j documentation](https://neo4j.com/docs/).\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DkeBdFEpi30I"
      },
      "source": [
        "## Configuration\n",
        "\n",
        "Do all the imports and configure OpenAI (enter your OpenAI API key):"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "d99EfBpii30I"
      },
      "outputs": [],
      "source": [
        "from mem0 import Memory\n",
        "\n",
        "import os\n",
        "\n",
        "os.environ[\"OPENAI_API_KEY\"] = (\n",
        "    \"\"\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QTucZJjIi30J"
      },
      "source": [
        "Set up configuration to use the embedder model and Neo4j as a graph store:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "QSE0RFoSi30J"
      },
      "outputs": [],
      "source": [
        "config = {\n",
        "    \"embedder\": {\n",
        "        \"provider\": \"openai\",\n",
        "        \"config\": {\"model\": \"text-embedding-3-large\", \"embedding_dims\": 1536},\n",
        "    },\n",
        "    \"graph_store\": {\n",
        "        \"provider\": \"neo4j\",\n",
        "        \"config\": {\n",
        "            \"url\": \"bolt://54.87.227.131:7687\",\n",
        "            \"username\": \"neo4j\",\n",
        "            \"password\": \"causes-bins-vines\",\n",
        "        },\n",
        "    },\n",
        "}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OioTnv6xi30J"
      },
      "source": [
        "## Graph Memory initializiation\n",
        "\n",
        "Initialize Neo4j as a Graph Memory store:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "fX-H9vgNi30J"
      },
      "outputs": [],
      "source": [
        "m = Memory.from_config(config_dict=config)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kr1fVMwEi30J"
      },
      "source": [
        "## Store memories\n",
        "\n",
        "Create memories:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "sEfogqp_i30J"
      },
      "outputs": [],
      "source": [
        "messages = [\n",
        "    {\n",
        "        \"role\": \"user\",\n",
        "        \"content\": \"I'm planning to watch a movie tonight. Any recommendations?\",\n",
        "    },\n",
        "    {\n",
        "        \"role\": \"assistant\",\n",
        "        \"content\": \"How about a thriller movies? They can be quite engaging.\",\n",
        "    },\n",
        "    {\n",
        "        \"role\": \"user\",\n",
        "        \"content\": \"I'm not a big fan of thriller movies but I love sci-fi movies.\",\n",
        "    },\n",
        "    {\n",
        "        \"role\": \"assistant\",\n",
        "        \"content\": \"Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future.\",\n",
        "    },\n",
        "]\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gtBHCyIgi30J"
      },
      "source": [
        "Store memories in Neo4j:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "BMVGgZMFi30K"
      },
      "outputs": [],
      "source": [
        "# Store inferred memories (default behavior)\n",
        "result = m.add(\n",
        "    messages, user_id=\"alice\"\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lQRptOywi30K"
      },
      "source": [
        "![](https://github.com/tomasonjo/mem0/blob/neo4jexample/examples/graph-db-demo/alice-memories.png?raw=1)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LBXW7Gv-i30K"
      },
      "source": [
        "## Search memories"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UHFDeQBEi30K",
        "outputId": "2c69de7d-a79a-48f6-e3c4-bd743067857c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Loves sci-fi movies 0.3153664287340898\n",
            "Planning to watch a movie tonight 0.09683349296551162\n",
            "Not a big fan of thriller movies 0.09468540071789466\n"
          ]
        }
      ],
      "source": [
        "for result in m.search(\"what does alice love?\", user_id=\"alice\")[\"results\"]:\n",
        "    print(result[\"memory\"], result[\"score\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "2jXEIma9kK_Q"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": ".venv",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.13.2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
